CAJ | 학술논문

高分辨雷达成像系统在当今的军事和民用方面都有着广泛的需求，高分辨率成像需要发射宽带的雷达信号，然而根据奈奎斯特采样定理，信号带宽的增加又使得雷达系统面临高采样率、高传输率、大数据量存储以及信号实时快速处理等问题。压缩感知(CS)理论通过构造非相关测量矩阵，以远低于奈奎斯特采样率的速率获得一组测量值，通过重构算法对信号进行精确的重构。压缩感知理论应用的前提是信号的稀疏性，关键是测量矩阵和稀疏度之间的关系，重要支撑是重构算法。本文对压缩感知原理进行了简要介绍并针对雷达常用的线性调频信号提出一种稀疏基构造方案。同时，利用 matlab构造了线性调频信号模型并对压缩感知处理线性调频信号的采样重建过程及应用于二维成像的过程进行了仿真。本文也研究了不同重建算法并进行了各个算法间的效果比较。仿真结果表明，在宽带雷达回波信号的处理过程中，压缩感知能通过降低采样率有效缓解回波数据的存储和传输的压力，这一点在宽带雷达目标检测中应用前景广阔。
고분변뢰체성상계통재당금적군사화민용방면도유착엄범적수구，고분변솔성상수요발사관대적뢰체신호，연이근거내규사특채양정리，신호대관적증가우사득뢰체계통면림고채양솔、고전수솔、대수거량존저이급신호실시쾌속처리등문제。압축감지(CS)이론통과구조비상관측량구진，이원저우내규사특채양솔적속솔획득일조측량치，통과중구산법대신호진행정학적중구。압축감지이론응용적전제시신호적희소성，관건시측량구진화희소도지간적관계，중요지탱시중구산법。본문대압축감지원리진행료간요개소병침대뢰체상용적선성조빈신호제출일충희소기구조방안。동시，이용 matlab구조료선성조빈신호모형병대압축감지처리선성조빈신호적채양중건과정급응용우이유성상적과정진행료방진。본문야연구료불동중건산법병진행료각개산법간적효과비교。방진결과표명，재관대뢰체회파신호적처리과정중，압축감지능통과강저채양솔유효완해회파수거적존저화전수적압력，저일점재관대뢰체목표검측중응용전경엄활。
High-resolution radar imaging system is widely used in both military and civil fields.Wide-band radar signals are necessary in high-resolution radar imaging,while these signals introduce high-sampling rate,high-transmission rate,large data storage and high difficulties to real time signal processing in radar system.These problems are resulted from Nyquist sampling theorem which requires the sampling rate to be more than two times of the bandwidth of the signal.As a consequence,searching for new signal processing and data acquisition methods is in urgent requirement.When dealing with some signals with the property of sparsity,the theory of compressed sensing which is different from the Nyquist sampling theorem,gets a group of numerical values through noncorrelation-measurement and the number of these measurements is much less than that of points sampled according to Nyquist sampling theorem.Then,we can reconstruct original-signal accurately by reconstruction-algorithms.The premise of using the theory of compressed sensing is the signal’s sparse property and the key to the theorem is the relationship between the measurement matrix and sparse degree.Meanwhile,the important support is the reconstruction algorithm.As we all know,response function of radar observations of the scene is usually sparse and this property leads to the sparsity of wide-band radar echo in some form.Based on this property,the application of the theory of compressed sensing in radar signal processing becomes possible.In this paper,the principle of signal sampling and reconstructing according to the theory of compressed sensing has been introduced briefly and a sparse matrix structure scheme for linear frequency modulation signal(LFM)commonly used in radar is proposed with the help of the emission signal.At the same time,the LFM signal model is structured with the help of MATLAB.Then,the processes of sampling and reconstruction of LFM and 2D imaging with the theory of compressed sensing are also simulated.Besides,this paper also studied the different reconstruction algorithms and makes the algorithm effectiveness comparison.The results show that during the process of broadband radar echo signal processing,the theory of compressed sensing can effectively relieve the pressure on the echo data storage and transmission through reducing sampling rate.This advantage can be widely used in wide-band radar target detection.